相似性(几何)
相似性度量
度量(数据仓库)
公理
数据挖掘
计算机科学
模糊集
模糊测度理论
模糊逻辑
功能(生物学)
数学
人工智能
隶属函数
理论计算机科学
图像(数学)
生物
进化生物学
几何学
作者
Minxia Luo,Xiaojing Gu,Wenling Li
摘要
As the theory of picture fuzzy sets has been developed, more information in life can be expressed in mathematical terms. Similarity measure is a special tool for quantifying the similarity between two sets, so studying similarity measure on picture fuzzy sets has become a trending topic. This new research direction has drawn a great deal of attention from experts and has led to a number of important results which have led to significant results in a number of practical applications. By examining these new findings, we discovered that there are many studies on similarity measure of picture fuzzy sets, some of them are deficient in solving certain problems, and such similarity measures can lead to the calculation of unreasonable data in practical applications, affecting the final results. Secondly, there is still room for research similarity measures on exponential functions. Considering these two aspects, we propose two new similarity measures based on exponential function, which not only satisfy the axiomatic definition of similarity measures, but also show reasonable computational results in practical applications.
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